Bringing together marine biodiversity, environmental and maritime boundaries data in R

Salvador Fernandez, Laura Marquez

May 30 2022

Bringing together marine biodiversity, environmental and maritime boundaries data in R

Salvador Fernandez, Laura Marquez, Lotte Pohl

May 30th 2022

The Story

The Story

The Story

The Story

The Story

The Story

Who we are

The Species

The Species

The Species

The Species

The Species

The Species

What we will learn

  1. How to access, query and obtain the data

  2. Visualize and get them ready for further exploration and analyses using R

  1. R packages:

Data Sources Overview

Exercises (TBD)

  1. Get and standardize data

  2. Get more occurrence data

    • EurOBIS: Get marine taxon occurrences

  3. Get environmental data

  4. Combine it all together

Exercises

Timeline (13:30 - 16:30)

  1. Introduction (13:30 - 14:00)

  2. Exercise 1 (14:00 - 14:45)

  3. Break (14:45 - 15:00)

  4. Exercise 2 (15:00 - 15:30)

  5. Exercise 3 (15:30 - 15:45)

  6. Coffee Break (15:45 - 16:00)

  7. Exercise 4 (16:30 - 16:15)

  8. Close-off (16:15 - 16:30)

Exercise 1

Use your own data!

Geospatial Data and Operations




Coordinate Reference Systems (CRS) provide a standardized way of describing locations.
https://www.nceas.ucsb.edu

AphiaID and MRGID



Exercise 2

Raster vs Vector Data



Dplyr

  • works with pipes (%>%) to increase code readability and avoid nesting
  • mean(as.numeric(df$temp)) translates to df$temp %>% as.numeric() %>% mean()
  • cheatsheet here

Exercise 3

Attention




Attention: raster::extract() and sf::st_join both do a spatial join. The former is used for raster data, the second one for vector data!

Exercise 4

Questions? Contact us!



And now have fun with the workshop!